MLOps Software Engineer

About the position

At Workday, we are looking for a Software Engineer to join our growth team focused on MLOps. This role involves building machine learning capabilities into our products, specifically within our HR & Talent product portfolio. You will work closely with ML engineers and other software teams to develop ML-powered features and experiences, utilizing modern MLOps, CloudOps, and data engineering stacks. Your responsibilities will include designing and developing new APIs/microservices, deploying them using Python, Terraform, and Kubernetes, and leveraging Workday's vast computing resources to deliver transformative value to our end-users.

Responsibilities

• Work with multi-functional teams to deliver scalable, secure, and reliable solutions.
• Build MLOps platform primarily using Kubeflow and other ML ecosystem tools for a unified ML Development experience.
• Engage with data scientists, ML engineers, PMs, and architects in requirements elaboration and drive technical solutions.
• Own and develop cloud-based services from end to end including infrastructure as code.
• Design and build software solutions for efficient organization, storage, and retrieval of data.
• Build systems and dashboards to monitor service & ML health.
• Lead in architecture reviews, code reviews, and technology evaluation.
• Research, evaluate, prototype, and drive adoption of new ML tools.

Requirements

• 5 or more years of validated industry experience.
• Bachelor's and/or Master's degree in Computer Science or Computer Engineering.
• Experience in designing, implementing, and maintaining robust MLOps services.
• Proficiency in public cloud-based infrastructure (AWS, GCP) to support machine learning workloads.
• Experience in building web applications and microservices and API design.
• 5 or more years of cloud programming experience preferably in Python or Go.
• Experience with running and maintaining Databricks, Sagemaker, & Apache Spark as a service.

Nice-to-haves

• Experience in managing relevant tools like Databricks and Sagemaker for large scale data lakes.
• Experience in leading or mentoring other team members.
• Ability to think across layers of the stack in data and/or ML systems.

Benefits

• Workday Bonus Plan eligibility.
• Annual refresh stock grants.
• Flexible work schedule with a combination of in-person and remote work.